Publikationen AS: Bibliographie 2016 BibTeX
@inproceedings {INPROC-2016-54,
author = {Henri Tokola and Christoph Gr{\"o}ger and Eeva J{\"a}rvenp{\"a}{\"a} and Esko Niemi},
title = {{Designing Manufacturing Dashboards on the Basis of a Key Performance Indicator Survey}},
booktitle = {Proceedings of the 49th CIRP Conference on Manufacturing Systems (CIRP CMS)},
publisher = {Elsevier},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
series = {Procedia CIRP},
volume = {57},
pages = {619--624},
type = {Konferenz-Beitrag},
month = {Mai},
year = {2016},
keywords = {Dashboards; Key Performance Indicators (KPIs); Scorecard},
language = {Englisch},
cr-category = {J.1 Administration Data Processing},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware},
abstract = {Target-oriented and real-time information provisioning across all hierarchy
levels, from shop floor to top floor, is an important success factory for
manufacturing companies to facilitate agile and efficient manufacturing. In
general, dashboards – in terms of digital single-screen displays – address this
challenge and support intuitive monitoring and visualisation of business
performance information. Yet, existing dashboard research mainly focus on IT
issues and lack a systematic study of the dashboard content. To address this
gap, in this paper, we design three representative dashboards for manufacturing
companies based on a comprehensive survey that focuses on suitable key
performance indicators for different manufacturing target groups. The paper
consists of three parts. First, the paper provides a literature review about
design principles of dashboards. Second, it publishes the results of a survey
of manufacturing companies on preferred key performance indicators (KPIs) for
dashboards and the use of dashboards. Third, using the results obtained from
the survey, three representative manufacturing dashboards are designed: an
operational dashboard for workers, a tactical dashboard for managers and a
strategy dashboard for executives. The results underline that different KPIs
are preferred for dashboards on different hierarchy levels and that mobile
usage of dashboards, especially on tablet pcs, is favoured.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-54&engl=0}
}
@inproceedings {INPROC-2016-42,
author = {Frank Steimle and Matthias Wieland},
title = {{ECHO – An mHealth Solution to Support Treatment of Chronic Patients}},
booktitle = {Proceedings of the 8th Central European Workshop on Services and their Composition, ZEUS 2016},
editor = {Christoph Hochreiner and Stefan Schulte},
publisher = {CEUR Workshop Proceedings},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
pages = {64--67},
type = {Demonstration},
month = {Februar},
year = {2016},
keywords = {mHealth; eHealth; Monitoring; Cloud Computing; Analysis},
language = {Deutsch},
cr-category = {C.2.4 Distributed Systems,
H.2.8 Database Applications,
J.3 Life and Medical Sciences},
ee = {http://ceur-ws.org/Vol-1562/},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware},
abstract = {More and more people all over the world suffer from chronic diseases, like
asthma. The German-Greek bilateral research project Enhancing Chronic Patients
Health Online developed online services for physicians and patients for use on
smart phones or web browsers, in order to improve monitoring of those patients
and to be able to detect possible exacerbations earlier. During the project we
have developed smart phone applications and websites for both patients and
physicians and a cloud-based health data management system. This demonstration
shows how our system supports physicians and patients.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-42&engl=0}
}
@inproceedings {INPROC-2016-39,
author = {Ana Cristina Franco da Silva and Uwe Breitenb{\"u}cher and K{\'a}lm{\'a}n K{\'e}pes and Oliver Kopp and Frank Leymann},
title = {{OpenTOSCA for IoT: Automating the Deployment of IoT Applications based on the Mosquitto Message Broker}},
booktitle = {Proceedings of the 6th International Conference on the Internet of Things (IoT)},
address = {Stuttgart},
publisher = {ACM},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
pages = {181--182},
type = {Demonstration},
month = {November},
year = {2016},
isbn = {978-1-4503-4814-0/16/11},
doi = {10.1145/2991561.2998464},
keywords = {Internet of Things; Cyber-Physical Systems; Sensor Integration; Message Broker; Mosquitto; MQTT; TOSCA},
language = {Englisch},
cr-category = {K.6 Management of Computing and Information Systems,
D.2.12 Software Engineering Interoperability},
contact = {For questions, feel free to contact me franco-da-silva@ipvs.uni-stuttgart.de},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware;
Universit{\"a}t Stuttgart, Institut f{\"u}r Architektur von Anwendungssystemen},
abstract = {Automating the deployment of IoT applications is a complex challenge,
especially if multiple heterogeneous sensors, actuators, and business
components have to be integrated. This demonstration paper presents a generic,
standards-based system that is able to fully automatically deploy IoT
applications based on the TOSCA standard, the standardized MQTT messaging
protocol, the Mosquitto message broker, and the runtime environment OpenTOSCA.
We describe a demonstration scenario and explain in detail how this scenario
can be deployed fully automatically using the mentioned technologies.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-39&engl=0}
}
@inproceedings {INPROC-2016-35,
author = {Jan K{\"o}nigsberger and Bernhard Mitschang},
title = {{A Semantically-enabled SOA Governance Repository}},
booktitle = {Proceedings of the 2016 IEEE 17th International Conference on Information Reuse and Integration},
editor = {IEEE Computer Society},
address = {Los Alamitos, California, Washington, Tokyo},
publisher = {IEEE Computer Society Conference Publishing Services},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
pages = {423--432},
type = {Konferenz-Beitrag},
month = {August},
year = {2016},
isbn = {978-1-5090-3207-5},
keywords = {SOA; Governance; Repository; Semantic Web},
language = {Englisch},
cr-category = {D.2.11 Software Engineering Software Architectures,
H.3.5 Online Information Services,
I.2.4 Knowledge Representation Formalisms and Methods},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware},
abstract = {Companies in today's world need to cope with an ever greater need for flexible
and agile IT systems to keep up with the competition and rapidly changing
markets. This leads to increasingly complex system landscapes that are often
realized using service-oriented architectures (SOA). Companies often struggle
to handle the complexity and the governance activities necessary after this
paradigm shift.
We therefore present a semantically-enabled SOA Governance Repository as the
central tool to manage and govern all SOA-related activities within a company.
This repository is based on our previously defined key governance aspects as
well as our SOA Governance Meta Model (SOA-GovMM). We describe how our
repository is able to support and improve the speed and flexibility of
company's IT processes.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-35&engl=0}
}
@inproceedings {INPROC-2016-30,
author = {Pascal Hirmer},
title = {{Flexible Execution and Modeling of Data Processing and Integration Flows}},
booktitle = {Proceedings of the 10th Advanced Summer School on Service Oriented Computing},
editor = {Johanna Barzen and Rania Khalaf and Frank Leymann and Bernhard Mitschang},
publisher = {IBM Research Report},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
pages = {26--40},
type = {Konferenz-Beitrag},
month = {September},
year = {2016},
keywords = {Big Data; Data Integration; Data Flows; Pipes and Filters},
language = {Englisch},
cr-category = {E.0 Data General,
E.1 Data Structures,
H.1 Models and Principles},
ee = {http://domino.research.ibm.com/library/cyberdig.nsf/papers/EC7D5D883519DC7E85258035004DBD19/$File/rc25624.pdf},
contact = {Pascal.Hirmer@ipvs.uni-stuttgart.de},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware},
abstract = {Today, the amount of data highly increases within all domains due to cheap
hardware, fast network connections, and an increasing digitization. Deriving
information and, as a consequence, knowledge from this huge amount of data is a
complex task. Data sources are oftentimes very heterogeneous, dynamic, and
distributed. This makes it difficult to extract, transform, process and
integrate data, which is necessary to gain this knowledge. Furthermore,
extracting knowledge oftentimes requires technical experts with the necessary
skills to conduct the required techniques. For my PhD thesis, I am working on a
new and improved approach for data extraction, processing, and integration by:
(i) facilitating the definition and processing of data processing and
integration scenarios through graphical creation of flow models, (ii) enabling
an ad-hoc, iterative and explorative approach to receive high-quality results,
and (iii) a flexible execution of the data processing tailor-made for users’
non-functional requirements. By providing these means, I enable a more flexible
data processing by a wider range of users, not only limited to technical
experts. This paper describes the approach of the thesis as well as the
publications until today.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-30&engl=0}
}
@inproceedings {INPROC-2016-29,
author = {Cornelia Kiefer},
title = {{Assessing the Quality of Unstructured Data: An Initial Overview}},
booktitle = {Proceedings of the LWDA 2016 Proceedings (LWDA)},
editor = {Ralf Krestel and Davide Mottin and Emmanuel M{\"u}ller},
address = {Aachen},
publisher = {CEUR Workshop Proceedings},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
pages = {62--73},
type = {Konferenz-Beitrag},
month = {September},
year = {2016},
isbn = {1613-0073},
keywords = {quality of unstructured data, quality of text data, data, quality dimensions, data quality assessment, data quality metrics},
language = {Englisch},
cr-category = {A.1 General Literature, Introductory and Survey,
I.2.7 Natural Language Processing},
ee = {http://ceur-ws.org/Vol-1670/paper-25.pdf,
http://ceur-ws.org/Vol-1670/},
contact = {cornelia.kiefer@gsame.uni-stuttgart.de},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware},
abstract = {In contrast to structured data, unstructured data such as texts, speech, videos
and pictures do not come with a data model that enables a computer to use them
directly. Nowadays, computers can interpret the knowledge encoded in
unstructured data using methods from text analytics, image recognition and
speech recognition. Therefore, unstructured data are used increasingly in
decision-making processes. But although decisions are commonly based on
unstructured data, data quality assessment methods for unstructured data are
lacking. We consider data analysis pipelines built upon two types of data
consumers, human consumers that usually come at the end of the pipeline and
non-human / machine consumers (e.g., natural language processing modules such
as part of speech tagger and named entity recognizer) that mainly work
intermediate. We define data quality of unstructured data via (1) the
similarity of the input data to the data expected by these consumers of
unstructured data and via (2) the similarity of the input data to the data
representing the real world. We deduce data quality dimensions from the
elements in analytic pipelines for unstructured data and characterize them.
Finally, we propose automatically measurable indicators for assessing the
quality of unstructured text data and give hints towards an implementation.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-29&engl=0}
}
@inproceedings {INPROC-2016-28,
author = {C. Timurhan Sungur and Uwe Breitenb{\"u}cher and Oliver Kopp and Frank Leymann and Mozi Song and Andreas Wei{\ss} and Christoph Mayr-Dorn and Schahram Dustdar},
title = {{Identifying Relevant Resources and Relevant Capabilities of Collaborations - A Case Study}},
booktitle = {Proceedings of the 2016 IEEE 20th International Enterprise Distributed Object Computing Workshop (EDOCW)},
publisher = {IEEE Computer Society},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
pages = {352--355},
type = {Demonstration},
month = {September},
year = {2016},
keywords = {Organizational performance; resource discovery; capability discovery; relevant resources; relevant capabilities; informal processes; unstructured processes},
language = {Englisch},
cr-category = {H.4.1 Office Automation,
H.3.3 Information Search and Retrieval,
H.3.4 Information Storage and Retrieval Systems and Software,
H.5.3 Group and Organization Interfaces},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware;
Universit{\"a}t Stuttgart, Institut f{\"u}r Architektur von Anwendungssystemen},
abstract = {Organizational processes involving collaborating resources, such as development
processes, innovation processes, and decision-making processes, typically
affect the performance of many organizations. Moreover, including required but
missing, resources and capabilities of collaborations can improve the
performance of corresponding processes drastically. In this work, we
demonstrate the extended Informal Process Execution (InProXec) method for
identifying resources and capabilities of collaborations using a case study on
the Apache jclouds project.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-28&engl=0}
}
@inproceedings {INPROC-2016-25,
author = {Pascal Hirmer and Matthias Wieland and Uwe Breitenb{\"u}cher and Bernhard Mitschang},
title = {{Dynamic Ontology-based Sensor Binding}},
booktitle = {Advances in Databases and Information Systems. 20th East European Conference, ADBIS 2016, Prague, Czech Republic, August 28-31, 2016, Proceedings},
address = {Prague, Czech Republic},
publisher = {Springer International Publishing},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
series = {Information Systems and Applications, incl. Internet/Web, and HCI},
volume = {9809},
pages = {323--337},
type = {Konferenz-Beitrag},
month = {August},
year = {2016},
isbn = {978-3-319-44039-2},
isbn = {978-3-319-44038-5},
doi = {10.1007/978-3-319-44039-2},
keywords = {Internet of Things; Sensors; Ontologies; Data Provisioning},
language = {Englisch},
cr-category = {E.0 Data General,
B.8 Performance and Reliability},
ee = {http://www.springer.com/de/book/9783319440385},
contact = {pascal.hirmer@ipvs.uni-stuttgart.de},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware;
Universit{\"a}t Stuttgart, Institut f{\"u}r Architektur von Anwendungssystemen},
abstract = {In recent years, the Internet of Things gains more and more attention through
cheap hardware devices and, consequently, an increased interconnection of them.
These devices equipped with sensors and actuators form the foundation for so
called smart environments that enable monitoring as well as self-organization.
However, an efficient sensor registration, binding, and sensor data
provisioning is still a major issue for the Internet of Things. Usually, these
steps can take up to days or even weeks due to a manual configuration and
binding by sensor experts that furthermore have to communicate with
domain-experts that define the requirements, e.g. the types of sensors, for the
smart environments. In previous work, we introduced a first vision of a method
for automated sensor registration, binding, and sensor data provisioning. In
this paper, we further detail and extend this vision, e.g., by introducing
optimization steps to enhance efficiency as well as effectiveness. Furthermore,
the approach is evaluated through a prototypical implementation.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-25&engl=0}
}
@inproceedings {INPROC-2016-24,
author = {Alexander Bergmayr and Uwe Breitenb{\"u}cher and Oliver Kopp and Manuel Wimmer and Gerti Kappel and Frank Leymann},
title = {{From Architecture Modeling to Application Provisioning for the Cloud by Combining UML and TOSCA}},
booktitle = {Proceedings of the 6th International Conference on Cloud Computing and Services Science (CLOSER 2016)},
publisher = {SCITEPRESS},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
pages = {97--108},
type = {Konferenz-Beitrag},
month = {April},
year = {2016},
doi = {10.5220/0005806900970108},
isbn = {978-989-758-182-3},
keywords = {TOSCA; UML; Model-Driven Software Engineering; Cloud Computing; Cloud Modeling},
language = {Englisch},
cr-category = {K.6 Management of Computing and Information Systems},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware;
Universit{\"a}t Stuttgart, Institut f{\"u}r Architektur von Anwendungssystemen},
abstract = {Recent efforts to standardize a deployment modeling language for cloud
applications resulted in TOSCA. At the same time, the software modeling
standard UML supports architecture modeling from different viewpoints.
Combining these standards from cloud computing and software engineering would
allow engineers to refine UML architectural models into TOSCA deployment models
that enable automatic provisioning of cloud applications. However, this
refinement task is currently carried out manually by recreating TOSCA models
from UML models because a conceptual mapping between the two languages as basis
for an automated translation is missing. In this paper, we exploit cloud
modeling extensions to UML called CAML as the basis for our approach
CAML2TOSCA, which aims at bridging UML and TOSCA. The validation of our
approach shows that UML models can directly be injected into a TOSCA-based
provisioning process. As current UML modeling tools lack cloud-based refinement
support for deployment models, the added value of CAML2TOSCA is emphasized
because it provides the glue between architecture modeling and application
provisioning.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-24&engl=0}
}
@inproceedings {INPROC-2016-22,
author = {Pascal Hirmer and Matthias Wieland and Uwe Breitenb{\"u}cher and Bernhard Mitschang},
title = {{Automated Sensor Registration, Binding and Sensor Data Provisioning}},
booktitle = {Proceedings of the CAiSE'16 Forum, at the 28th International Conference on Advanced Information Systems Engineering (CAiSE 2016)},
address = {Ljubljana, Slovenia},
publisher = {CEUR-WS.org},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
series = {CEUR Workshop Proceedings},
volume = {1612},
pages = {81--88},
type = {Konferenz-Beitrag},
month = {Juni},
year = {2016},
issn = {1613-0073},
keywords = {Internet of Things; Sensors; Ontologies; Data Provisioning},
language = {Englisch},
cr-category = {J.6 Computer-Aided Engineering,
H.3.1 Content Analysis and Indexing},
ee = {http://ceur-ws.org/Vol-1612/paper11.pdf},
contact = {pascal.hirmer@ipvs.uni-stuttgart.de},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware},
abstract = {Today, the Internet of Things has evolved due to an increasing interconnection
of technical devices. However, the automated binding and management of things
and sensors is still a major issue. In this paper, we present a method and
system architecture for sensor registration, binding, and sensor data
provisioning. This approach enables automated sensor integration and data
processing by accessing the sensors and provisioning the data. Furthermore, the
registration of new sensors is done in an automated way to avoid a complex,
tedious manual registration. We enable (i) semantic description of sensors and
things as well as their attributes using ontologies, (ii) the registration of
sensors of a physical thing, (iii) a provisioning of sensor data using
different data access paradigms, and (iv) dynamic sensor binding based on
application requirements. We provide the Resource Management Platform as a
prototypical implementation of the architecture and corresponding runtime
measurements},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-22&engl=0}
}
@inproceedings {INPROC-2016-21,
author = {C. Timurhan Sungur and Uwe Breitenb{\"u}cher and Frank Leymann and Matthias Wieland},
title = {{Context-sensitive Adaptive Production Processes}},
booktitle = {Proceedings of the 48th CIRP Conference on Manufacturing Systems},
publisher = {Elsevier},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
series = {Procedia CIRP},
volume = {41},
pages = {147--152},
type = {Konferenz-Beitrag},
month = {Februar},
year = {2016},
doi = {10.1016/j.procir.2015.12.076},
keywords = {Process; Automation; Optimization; Adaptation},
language = {Englisch},
cr-category = {H.4.1 Office Automation,
H.5.3 Group and Organization Interfaces},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware;
Universit{\"a}t Stuttgart, Institut f{\"u}r Architektur von Anwendungssystemen},
abstract = {To stay competitive, manufacturing companies need to adapt their processes in a
regular basis to the most recent conditions in their corresponding domains.
These adaptations are typically the result of turbulences, such as changes in
human resources, new technological advancements, or economic crises. Therefore,
to increase the efficiency of production processes, (i) automation, (ii)
optimization, and (iii) dynamic adaptation became the most important
requirements in this field. In this work, we propose a novel process modelling
and execution approach for creating self-organizing processes: Production
processes are extended by context-sensitive execution steps, for which
sub-processes are selected, elected, optimized, and finally executed on
runtime. During the election step, the most desired solution is chosen and
optimized based on selection and optimization strategies of the respective
processes. Moreover, we present a system architecture for modelling and
executing these context-sensitive production processes.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-21&engl=0}
}
@inproceedings {INPROC-2016-10,
author = {Christoph Stach},
title = {{Secure Candy Castle - A Prototype for Privacy-Aware mHealth Apps}},
booktitle = {Proceedings of the 17th International Conference on Mobile Data Management},
address = {Porto},
publisher = {IEEE Computer Society Conference Publishing Services},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
pages = {361--364},
type = {Demonstration},
month = {Juni},
year = {2016},
keywords = {mHealth; privacy; diagnostic game; diabetes},
language = {Englisch},
cr-category = {K.4.1 Computers and Society Public Policy Issues,
D.4.6 Operating Systems Security and Protection,
K.8 Personal Computing,
J.3 Life and Medical Sciences},
contact = {Senden Sie eine E-Mail an Christoph.Stach@ipvs.uni-stuttgart.de},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware},
abstract = {Due to rising medical costs, the healthcare landscape is on the move. Novel
treatment methods are badly required. Especially for the treatment of chronic
diseases the usage of smart devices in combination with medical devices for
telemedical screenings is a promising approach. If the patients are not in
control of the collection and processing of their health data, privacy concerns
limit their willingness to use such a method. In this paper, we present a
prototype for an Android-based privacy-aware health game for children suffering
from diabetes called Secure Candy Castle. In the game, the player keeps an
electronic diabetes diary in a playful manner. In doing this, s/he is supported
by various sensors. His or her data is analyzed and in case of a critical
health condition, the game notifies authorized persons. With our approach, the
user stays in control over his or her data, i.e., s/he defines which data
should be shared with the game, how accurate this data should be, and even how
the data is processed by the game. For this purpose, we apply the Privacy
Management Platform, a fine-grained and extendable permission system.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-10&engl=0}
}
@inproceedings {INPROC-2016-09,
author = {Christoph Stach and Bernhard Mitschang},
title = {{The Secure Data Container: An Approach to Harmonize Data Sharing with Information Security}},
booktitle = {Proceedings of the 17th International Conference on Mobile Data Management},
address = {Porto},
publisher = {IEEE Computer Society Conference Publishing Services},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
pages = {292--297},
type = {Konferenz-Beitrag},
month = {Juni},
year = {2016},
keywords = {smart devices; information security; data sharing},
language = {Englisch},
cr-category = {K.4.1 Computers and Society Public Policy Issues,
D.4.6 Operating Systems Security and Protection},
contact = {Senden Sie eine E-Mail an Christoph.Stach@ipvs.uni-stuttgart.de},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware},
abstract = {Smart devices became Marc Weiser's Computer of the 21st Century. Due to their
versatility a lot of private data enriched by context data are stored on them.
Even the health industry utilizes smart devices as portable health monitors and
enablers for telediagnosis. So they represent a severe risk for information
security. Yet the platform providers' countermeasures to these threats are by
no means sufficient. In this paper we describe how information security can be
improved. Therefore, we postulate requirements towards a secure handling of
data. Based on this requirements specification, we introduce a secure data
container as an extension for the Privacy Management Platform. Since a complete
isolation of an app is usually not practicable, our approach also provides
secure data sharing features. Finally, we evaluate our approach from a
technical point of view as well as a security point of view and show its
applicability in an eHealth scenario.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-09&engl=0}
}
@inproceedings {INPROC-2016-07,
author = {Christoph Gr{\"o}ger and Laura Kassner and Eva Hoos and Jan K{\"o}nigsberger and Cornelia Kiefer and Stefan Silcher and Bernhard Mitschang},
title = {{The Data-Driven Factory. Leveraging Big Industrial Data for Agile, Learning and Human-Centric Manufacturing}},
booktitle = {Proceedings of the 18th International Conference on Enterprise Information Systems},
editor = {Slimane Hammoudi and Leszek Maciaszek and Michele M. Missikoff and Olivier Camp and Jose Cordeiro},
publisher = {SciTePress},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
pages = {40--52},
type = {Konferenz-Beitrag},
month = {April},
year = {2016},
isbn = {978-989-758-187-8},
keywords = {IT Architecture, Data Analytics, Big Data, Smart Manufacturing, Industrie 4.0},
language = {Englisch},
cr-category = {H.4.0 Information Systems Applications General,
J.2 Physical Sciences and Engineering},
contact = {Email an Christoph.Groeger@ipvs.uni-stuttgart.de oder laura.kassner@ipvs.uni-stuttgart.de},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware},
abstract = {Global competition in the manufacturing industry is characterized by ever
shorter product life cycles, increas-ing complexity and a turbulent
environment. High product quality, continuously improved processes as well as
changeable organizational structures constitute central success factors for
manufacturing companies. With the rise of the internet of things and Industrie
4.0, the increasing use of cyber-physical systems as well as the digitalization
of manufacturing operations lead to massive amounts of heterogeneous industrial
data across the product life cycle. In order to leverage these big industrial
data for competitive advantages, we present the concept of the data-driven
factory. The data-driven factory enables agile, learning and human-centric
manu-facturing and makes use of a novel IT architecture, the Stuttgart IT
Architecture for Manufacturing (SITAM), overcoming the insufficiencies of the
traditional information pyramid of manufacturing. We introduce the SITAM
architecture and discuss its conceptual components with respect to
service-oriented integration, ad-vanced analytics and mobile information
provisioning in manufacturing. Moreover, for evaluation purposes, we present a
prototypical implementation of the SITAM architecture as well as a real-world
application sce-nario from the automotive industry to demonstrate the benefits
of the data-driven factory.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-07&engl=0}
}
@inproceedings {INPROC-2016-06,
author = {Laura Kassner and Bernhard Mitschang},
title = {{Exploring Text Classification for Messy Data: An Industry Use Case for Domain-Specific Analytics}},
booktitle = {Advances in Database Technology - EDBT 2016, 19th International Conference on Extending Database Technology, Bordeaux, France, March 15-16, Proceedings},
publisher = {OpenProceedings.org},
institution = {Universit{\"a}t Stuttgart, Fakult{\"a}t Informatik, Elektrotechnik und Informationstechnik, Germany},
pages = {491--502},
type = {Konferenz-Beitrag},
month = {M{\"a}rz},
year = {2016},
isbn = {978-3-89318-070-7},
keywords = {recommendation system; automotive; text analytics; domain-specific language; automatic classification},
language = {Englisch},
cr-category = {H.3.1 Content Analysis and Indexing,
H.3.3 Information Search and Retrieval,
H.4.2 Information Systems Applications Types of Systems,
J.1 Administration Data Processing},
ee = {http://openproceedings.org/2016/conf/edbt/paper-52.pdf},
contact = {Email an laura.kassner@ipvs.uni-stuttgart.de},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware},
abstract = {Industrial enterprise data present classification problems which are different
from those problems typically discussed in the scientific community -- with
larger amounts of classes and with domain-specific, often unstructured data. We
address one such problem through an analytics environment which makes use of
domain-specific knowledge. Companies are beginning to use analytics on large
amounts of text data which they have access to, but in day-to-day business,
manual effort is still the dominant method for processing unstructured data. In
the face of ever larger amounts of data, faster innovation cycles and higher
product customization, human experts need to be supported in their work through
data analytics. In cooperation with a large automotive manufacturer, we have
developed a use case in the area of quality management for supporting human
labor through text analytics: When processing damaged car parts for quality
improvement and warranty handling, quality experts have to read text reports
and assign error codes to damaged parts. We design and implement a system to
recommend likely error codes based on the automatic recognition of error
mentions in textual quality reports. In our prototypical implementation, we
test several methods for filtering out accurate recommendations for error codes
and develop further directions for applying this method to a competitive
business intelligence use case.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INPROC-2016-06&engl=0}
}
@article {ART-2016-26,
author = {Uwe Breitenb{\"u}cher and Christian Endres and K{\'a}lm{\'a}n K{\'e}pes and Oliver Kopp and Frank Leymann and Sebastian Wagner and Johannes Wettinger and Michael Zimmermann},
title = {{The OpenTOSCA Ecosystem - Concepts \& Tools}},
journal = {European Space project on Smart Systems, Big Data, Future Internet - Towards Serving the Grand Societal Challenges - Volume 1: EPS Rome 2016},
publisher = {SciTePress},
pages = {112--130},
type = {Artikel in Zeitschrift},
month = {Dezember},
year = {2016},
isbn = {978-989-758-207-3},
doi = {10.5220/0007903201120130},
keywords = {TOSCA; OpenTOSCA; Orchestration; Management; Cloud},
language = {Englisch},
cr-category = {D.2.2 Software Engineering Design Tools and Techniques,
D.2.9 Software Engineering Management},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware;
Universit{\"a}t Stuttgart, Institut f{\"u}r Architektur von Anwendungssystemen},
abstract = {Automating the provisioning and management of Cloud applications is one of the
most important issues in Cloud Computing. The Topology and Orchestration
Specification for Cloud Applications (TOSCA) is an OASIS standard for
describing Cloud applications and their management in a portable and
interoperable manner. TOSCA enables modeling the application's structure in the
form of topology models and employs the concept of executable management plans
to describe all required management functionality regarding the application. In
this paper, we give an overview of TOSCA and the OpenTOSCA Ecosystem, which is
an implementation of the TOSCA standard. The ecosystem consists of
standard-compliant tools that enable modeling application topology models and
automating the provisioning and management of the modeled applications.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2016-26&engl=0}
}
@article {ART-2016-23,
author = {Pascal Hirmer and Uwe Breitenb{\"u}cher and Ana Cristina Franco da Silva and K{\'a}lm{\'a}n K{\'e}pes and Bernhard Mitschang and Matthias Wieland},
title = {{Automating the Provisioning and Configuration of Devices in the Internet of Things}},
journal = {Complex Systems Informatics and Modeling Quarterly},
publisher = {Online},
volume = {9},
pages = {28--43},
type = {Artikel in Zeitschrift},
month = {Dezember},
year = {2016},
doi = {10.7250/csimq.2016-9.02},
issn = {2255 - 9922},
keywords = {Internet of Things; sensors; actuators; digital twin; ontologies; TOSCA},
language = {Englisch},
cr-category = {J.6 Computer-Aided Engineering,
H.3.1 Content Analysis and Indexing},
ee = {https://csimq-journals.rtu.lv/article/view/csimq.2016-9.02/pdf_8},
contact = {pascal.hirmer@ipvs.uni-stuttgart.de},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware},
abstract = {The Internet of Things benefits from an increasing number of interconnected
technical devices. This has led to the existence of so-called smart
environments, which encompass one or more devices sensing, acting, and
automatically performing different tasks to enable their self-organization.
Smart environments are divided into two parts: the physical environment and its
digital representation, oftentimes referred to as digital twin. However, the
automated binding and monitoring of devices of smart environments are still
major issues. In this article we present a method and system architecture to
cope with these challenges by enabling (i) easy modeling of sensors, actuators,
devices, and their attributes, (ii) dynamic device binding based on their type,
(iii) the access to devices using different paradigms, and (iv) the monitoring
of smart environments in regard to failures or changes. We furthermore provide
a prototypical implementation of the introduced approach.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2016-23&engl=0}
}
@article {ART-2016-19,
author = {Marina Bitsaki and Christos Koutras and George Koutras and Frank Leymann and Frank Steimle and Sebastian Wagner and Matthias Wieland},
title = {{ChronicOnline: Implementing a mHealth solution for monitoring and early alerting in chronic obstructive pulmonary disease}},
journal = {Health Informatics Journal},
publisher = {Sage Publications},
pages = {1--10},
type = {Artikel in Zeitschrift},
month = {April},
year = {2016},
doi = {10.1177/1460458216641480},
keywords = {chronic obstructive pulmonary disease; cloud computing; health services; mobile applications; monitoring},
language = {Englisch},
cr-category = {C.2.4 Distributed Systems,
H.2.8 Database Applications,
J.3 Life and Medical Sciences},
ee = {http://jhi.sagepub.com/content/early/2016/04/16/1460458216641480.full.pdf+html},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware;
Universit{\"a}t Stuttgart, Institut f{\"u}r Architektur von Anwendungssystemen},
abstract = {Lack of time or economic difficulties prevent chronic obstructive pulmonary
disease patients from communicating regularly with their physicians, thus
inducing exacerbation of their chronic condition and possible hospitalization.
Enhancing Chronic patients{\^a}€™ Health Online proposes a new, sustainable and
innovative business model that provides at low cost and at significant savings
to the national health system, a preventive health service for chronic
obstructive pulmonary disease patients, by combining human medical expertise
with state-of-the-art online service delivery based on cloud computing,
service-oriented architecture, data analytics, and mobile applications. In this
article, we implement the frontend applications of the Enhancing Chronic
patients{\^a}€™ Health Online system and describe their functionality and the
interfaces available to the users.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2016-19&engl=0}
}
@article {ART-2016-18,
author = {Frank Steimle and Matthias Wieland and Bernhard Mitschang and Sebastian Wagner and Frank Leymann},
title = {{Extended provisioning, security and analysis techniques for the ECHO health data management system}},
journal = {Computing},
publisher = {Springer},
pages = {1--19},
type = {Artikel in Zeitschrift},
month = {Oktober},
year = {2016},
doi = {10.1007/s00607-016-0523-8},
language = {Englisch},
cr-category = {C.2.4 Distributed Systems,
H.2.8 Database Applications,
J.3 Life and Medical Sciences},
ee = {http://dx.doi.org/10.1007/s00607-016-0523-8},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware},
abstract = {eHealth gains more and more interest since a lot of end-user devices supporting
health data capturing are available. The captured data has to be managed and
securely stored, in order to access it from different devices and share it with
other users such as physicians. The aim of the german-greek research project
ECHO is to support the treatment of patients, who suffer from chronic
obstructive pulmonary disease, a chronic respiratory disease. Usually the
patients need to be examined by their physicians on a regular basis due to
their chronic condition. Since this is very time consuming and expensive we
developed an eHealth system which allows the physician to monitor patients
condition remotely, e.g., via smart phones. This article is an extension of
previous work, where we introduced a health data model and an associated
platform-architecture for the management and analysis of the data provided by
the patients. There we have also shown how the security of the data is ensured
and we explained how the platform can be provided in a cloud-based environment
using the OASIS standard TOSCA, which enables a self-contained management of
cloud-services. In this article we provide a more detailed description about
the health data analysis, provisioning and security aspects of the eHealth
system.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2016-18&engl=0}
}
@article {ART-2016-16,
author = {Mathias Mormul and Pascal Hirmer and Matthias Wieland and Bernhard Mitschang},
title = {{Situation model as interface between situation recognition and situation-aware applications}},
journal = {Computer Science - Research and Development},
publisher = {Springer Berlin Heidelberg},
pages = {1--12},
type = {Artikel in Zeitschrift},
month = {November},
year = {2016},
doi = {10.1007/s00450-016-0335-2},
keywords = {Situation; Situation-awareness; Data management; Internet of things; Context; Context-awareness},
language = {Englisch},
cr-category = {J.6 Computer-Aided Engineering,
H.3.1 Content Analysis and Indexing},
ee = {http://link.springer.com/article/10.1007/s00450-016-0335-2},
contact = {pascal.hirmer@ipvs.uni-stuttgart.de},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware},
abstract = {The upcoming of internet of things draws interest of many companies and leads
to the creation of smart environments. The foundation necessary for this
purpose lies in the integration of sensors, which continuously provide context
data of their environment. Based on this context, changes of state in the
environment, i.e., situations, can be detected. However, with the huge amount
of heterogeneous context and its processing, new challenges arise.
Simultaneously, the dynamic behavior of the environment demands automated
mechanisms for applications to adapt to the situations automatically and in a
timely manner. To meet this challenge, we present (1) the situation model as a
data model for integrating all data related to situation recognition, and (2)
the management and provisioning of situations based on this situation model to
further decouple situation recognition and applications adapting to recognized
situations. Furthermore, we present a prototypical implementation of the
situation model and its management.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2016-16&engl=0}
}
@article {ART-2016-14,
author = {Ana Cristina Franco da Silva and Pascal Hirmer and Matthias Wieland and Bernhard Mitschang},
title = {{SitRS XT – Towards Near Real Time Situation Recognition}},
journal = {Journal of Information and Data Management},
publisher = {-},
volume = {7},
number = {1},
pages = {4--17},
type = {Artikel in Zeitschrift},
month = {April},
year = {2016},
keywords = {Complex Event Processing; Internet of Things; Situation-awareness; Situation Recognition},
language = {Englisch},
cr-category = {H.3 Information Storage and Retrieval,
I.5 Pattern Recognition},
ee = {https://seer.lcc.ufmg.br/index.php/jidm/article/view/2109},
contact = {franco-da-silva@ipvs.uni-stuttgart.de},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware},
abstract = {Nowadays, the Internet of Things gains more and more attention through cheap,
highly interconnected hardware devices that are attached with sensors and
actuators. This results in an instrumented environment that provides sufficient
context information to drive what is called situation recognition. Situations
are derived from large amounts of context data, which is difficult to handle.
In this article, we present SitRS XT, an extension of our previously introduced
situation recognition service SitRS, to enable situation recognition in near
real time. SitRS XT provides easy to use situation recognition based on Complex
Event Processing, which is highly efficient. The architecture and method of
SitRS XT is described and evaluated through a prototypical implementation.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2016-14&engl=0}
}
@article {ART-2016-13,
author = {Pascal Hirmer and Bernhard Mitschang},
title = {{TOSCA4Mashups: enhanced method for on-demand data mashup provisioning}},
journal = {Computer Science - Research and Development},
publisher = {Springer Berlin Heidelberg},
pages = {1--10},
type = {Artikel in Zeitschrift},
month = {Oktober},
year = {2016},
doi = {10.1007/s00450-016-0330-7},
keywords = {Data Mashups; TOSCA; Provisioning; Cloud Computing},
language = {Englisch},
cr-category = {E.0 Data General,
E.1 Data Structures,
H.1 Models and Principles},
ee = {http://link.springer.com/article/10.1007/s00450-016-0330-7},
contact = {Pascal.Hirmer@ipvs.uni-stuttgart.de},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware},
abstract = {Nowadays, the amount of data increases tremendously. Extracting information and
generating knowledge from this data is a great challenge. To cope with this
issue – oftentimes referred to as big data problem – we need effective means
for efficient data integration, data processing, and data analysis. To enable
flexible, explorative and ad-hoc data processing, several data mashup
approaches and tools have been developed in the past. One of these tools is
FlexMash – a data mashup tool developed at the University of Stuttgart. By
offering domain-specific graphical modeling as well as a pattern-based
execution, FlexMash enables usage by a wide range of users, both domain experts
and technical experts. The core idea of FlexMash is a flexible execution of
data mashups using different, user-requirement-dependent execution components.
In this paper, we present a new approach for on-demand, automated provisioning
of these components in a cloud computing environment using the Topology and
Orchestration Specification for Cloud Applications. This enables many
advantages for mashup execution such as scalability, availability and cost
savings.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2016-13&engl=0}
}
@article {ART-2016-12,
author = {Pascal Hirmer and Matthias Wieland and Holger Schwarz and Bernhard Mitschang and Uwe Breitenb{\"u}cher and Santiago G{\'o}mez S{\'a}ez and Frank Leymann},
title = {{Situation recognition and handling based on executing situation templates and situation-aware workflows}},
journal = {Computing},
publisher = {Springer},
pages = {1--19},
type = {Artikel in Zeitschrift},
month = {Oktober},
year = {2016},
doi = {10.1007/s00607-016-0522-9},
keywords = {Situation Recognition; IoT; Context; Integration; Cloud Computing; Workflows; Middleware},
language = {Englisch},
cr-category = {J.6 Computer-Aided Engineering,
H.3.1 Content Analysis and Indexing},
ee = {http://dx.doi.org/10.1007/s00607-016-0522-9},
contact = {pascal.hirmer@ipvs.uni-stuttgart.de},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware},
abstract = {Today, the Internet of Things has evolved due to an advanced interconnectivity
of hardware devices equipped with sensors and actuators. Such connected
environments are nowadays well-known as smart environments. Famous examples are
smart homes, smart cities, and smart factories. Such environments should only
be called {\ss}mart`` if they allow monitoring and self-organization. However, this
is a great challenge: (1) sensors have to be bound and sensor data have to be
efficiently provisioned to enable monitoring of these environments, (2)
situations have to be detected based on sensor data, and (3) based on the
recognized situations, a reaction has to be triggered to enable
self-organization, e.g., through notification delivery or the execution of
workflows. In this article, we introduce SitOPT---an approach for situation
recognition based on raw sensor data and automated handling of occurring
situations through notification delivery or execution of situation-aware
workflows. This article is an extended version of the paper ''SitRS - Situation
Recognition based on Modeling and Executing Situation Templates`` presented at
the 9th Symposium and Summer School of Service-oriented Computing 2015.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2016-12&engl=0}
}
@article {ART-2016-10,
author = {Christoph Hochreiner and Stefan Schulte and Oliver Kopp},
title = {{Bericht zum 8. ZEUS Workshop}},
journal = {Softwaretechnik-Trends},
publisher = {Online},
volume = {36},
number = {2},
pages = {61--62},
type = {Artikel in Zeitschrift},
month = {August},
year = {2016},
issn = {0720-8928},
language = {Deutsch},
cr-category = {H.4.1 Office Automation},
ee = {http://pi.informatik.uni-siegen.de/gi/stt/36_2/03_Technische_Beitraege/ZEUS2016/bericht_zeus.pdf,
http://pi.informatik.uni-siegen.de/gi/stt/36_2/index.html},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware},
abstract = {Es wird {\"u}ber den 8. ZEUS Workshop in Wien im Speziellen und dem ZEUS Workshop
als Konzept im Allgemeinen berichtet.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2016-10&engl=0}
}
@article {ART-2016-06,
author = {Christoph Gr{\"o}ger and Christoph Stach and Bernhard Mitschang and Engelbert Westk{\"a}mper},
title = {{A mobile dashboard for analytics-based information provisioning on the shop floor}},
journal = {International Journal of Computer Integrated Manufacturing},
publisher = {Taylor \& Francis Inc.},
pages = {1--20},
type = {Artikel in Zeitschrift},
month = {Mai},
year = {2016},
doi = {10.1080/0951192X.2016.1187292},
keywords = {dashboard; cockpit; process optimisation; data analytics; business intelligence; data mining},
language = {Englisch},
cr-category = {H.4.0 Information Systems Applications General,
J.2 Physical Sciences and Engineering},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware},
abstract = {Today's turbulent global environment requires agility and flexibility of
manufacturing companies to stay competitive. Thus, employees have to monitor
their performance continuously and react quickly to turbulences which demands
real-time information provisioning across all hierarchy levels. However,
existing manufacturing IT systems, for example, manufacturing execution systems
(MES), do hardly address information needs of individual employees on the shop
floor. Besides, they do not exploit advanced analytics to generate novel
insights for process optimisation. To address these issues, the operational
process dashboard for manufacturing (OPDM) is presented, a mobile
data-mining-based dashboard for workers and supervisors on the shop floor. It
enables proactive optimisation by providing analytical information anywhere and
anytime in the factory. In this paper, first, user groups and conceptual
dashboard services are defined. Then, IT design issues of a mobile shop floor
application on top of the advanced manufacturing analytics platform are
investigated in order to realise the OPDM. This comprises the evaluation of
different types of mobile devices, the development of an appropriate context
model and the investigation of security issues. Finally, an evaluation in an
automotive industry case is presented using a prototype in order to demonstrate
the benefits of the OPDM for data-driven process improvement and agility in
manufacturing.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=ART-2016-06&engl=0}
}
@inbook {INBOOK-2016-04,
author = {Uwe Breitenb{\"u}cher and Tobias Binz and Oliver Kopp and K{\'a}lm{\'a}n K{\'e}pes and Frank Leymann and Johannes Wettinger},
title = {{Hybrid TOSCA Provisioning Plans: Integrating Declarative and Imperative Cloud Application Provisioning Technologies}},
series = {Cloud Computing and Services Science},
publisher = {Springer International Publishing},
series = {Communications in Computer and Information Science},
volume = {581},
pages = {239--262},
type = {Beitrag in Buch},
month = {Februar},
year = {2016},
doi = {10.1007/978-3-319-29582-4_13},
isbn = {978-3-319-29581-7},
keywords = {Cloud application provisioning; TOSCA; Hybrid plans; Automation; Declarative modelling; Imperative modelling; Integration},
language = {Englisch},
cr-category = {K.6 Management of Computing and Information Systems},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware;
Universit{\"a}t Stuttgart, Institut f{\"u}r Architektur von Anwendungssystemen},
abstract = {The efficient provisioning of complex applications is one of the most
challenging issues in Cloud Computing. Therefore, various provisioning and
configuration management technologies have been developed that can be
categorized as follows: imperative approaches enable a precise specification of
the low-level tasks to be executed whereas declarative approaches focus on
describing the desired goals and constraints. Since complex applications employ
a plethora of heterogeneous components that must be wired and configured,
typically multiple of these technologies have to be integrated to automate the
entire provisioning process. In a former work, we presented a workflow
modelling concept that enables the seamless integration of imperative and
declarative technologies. This paper is an extension of that work to integrate
the modelling concept with the Cloud standard TOSCA. In particular, we show how
Hybrid Provisioning Plans can be created that retrieve all required information
about the desired provisioning directly from the corresponding TOSCA model. We
validate the practical feasibility of the concept by extending the OpenTOSCA
runtime environment and the workflow language BPEL.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INBOOK-2016-04&engl=0}
}
@inbook {INBOOK-2016-01,
author = {Pascal Hirmer and Bernhard Mitschang},
title = {{FlexMash - Flexible Data Mashups Based on Pattern-Based Model Transformation}},
series = {Rapid Mashup Development Tools},
publisher = {Springer International Publishing},
series = {Communications in Computer and Information Science},
volume = {591},
pages = {12--30},
type = {Beitrag in Buch},
month = {Februar},
year = {2016},
isbn = {978-3-319-28726-3},
doi = {10.1007/978-3-319-28727-0_2},
keywords = {ICWE rapid mashup challenge 2015; Data mashups; Transformation patterns; TOSCA; Cloud computing},
language = {Englisch},
cr-category = {H.2.8 Database Applications,
H.3.0 Information Storage and Retrieval General,
E.1 Data Structures},
ee = {http://dx.doi.org/10.1007/978-3-319-28727-0_2},
department = {Universit{\"a}t Stuttgart, Institut f{\"u}r Parallele und Verteilte Systeme, Anwendersoftware},
abstract = {Today, the ad-hoc processing and integration of data is an important issue due
to fast growing IT systems and an increased connectivity of the corresponding
data sources. The overall goal is deriving high-level information based on a
huge amount of low-level data. However, an increasing amount of data leads to
high complexity and many technical challenges. Especially non-IT expert users
are overburdened with highly complex solutions such as Extract-Transform-Load
processes. To tackle these issues, we need a means to abstract from technical
details and provide a flexible execution of data processing and integration
scenarios. In this paper, we present an approach for modeling and pattern-based
execution of data mashups based on Mashup Plans, a domain-specific mashup model
that has been introduced in previous work. This non-executable model can be
mapped onto different executable ones depending on the use case scenario. The
concepts introduced in this paper were presented during the Rapid Mashup
Challenge at the International Conference on Web Engineering 2015. This paper
presents our approach, the scenario that was implemented for this challenge, as
well as the encountered issues during its preparation.},
url = {http://www2.informatik.uni-stuttgart.de/cgi-bin/NCSTRL/NCSTRL_view.pl?id=INBOOK-2016-01&engl=0}
}
